The precipitation map - updated every 6 hours - shows the modeled precipitation in mm.
The precipitation areas are encircled
by isohyets - lines with equal amounts of precipitation. However, modeling precipitation is
still not very reliable. If you compare the modeled results with observed values you will
realize that the model is nothing better than a first order approach. Yet this chart is of some
use for forecasters.
Note: Based on international convention meteorologists use the metric system. 100 mm of
precipitation is equivalent to roughly 4 inches.

GFS:

The Global Forecast System (GFS) is a global numerical weather prediction computer model run by NOAA. This mathematical model is run four times a day and produces forecasts up to 16 days in advance, but with decreasing spatial and temporal resolution over time it is widely accepted that beyond 7 days the forecast is very general and not very accurate.

The model is run in two parts: the first part has a higher resolution and goes out to 180 hours (7 days) in the future, the second part runs from 180 to 384 hours (16 days) at a lower resolution. The resolution of the model varies in each part of the model: horizontally, it divides the surface of the earth into 35 or 70 kilometre grid squares; vertically, it divides the atmosphere into 64 layers and temporally, it produces a forecast for every 3rd hour for the first 180 hours, after that they are produced for every 12th hour.

NWP:

Numerical weather prediction uses current weather conditions as input into mathematical models of the atmosphere to predict the weather. Although the first efforts to accomplish this were done in the 1920s, it wasn't until the advent of the computer and computer simulation that it was feasible to do in real-time. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful requires the use of some of the most powerful supercomputers in the world. A number of forecast models, both global and regional in scale, are run to help create forecasts for nations worldwide. Use of model ensemble forecasts helps to define the forecast uncertainty and extend weather forecasting farther into the future than would otherwise be possible.